Uses of Class
org.deeplearning4j.nn.layers.BaseOutputLayer

Packages that use BaseOutputLayer

Package	Description
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.layers.training

Uses of BaseOutputLayer in org.deeplearning4j.nn.layers

Subclasses of BaseOutputLayer in org.deeplearning4j.nn.layers

Modifier and Type	Class and Description
class	OutputLayer Output layer with different objective incooccurrences for different objectives.

Uses of BaseOutputLayer in org.deeplearning4j.nn.layers.recurrent

Subclasses of BaseOutputLayer in org.deeplearning4j.nn.layers.recurrent

Modifier and Type	Class and Description
class	RnnOutputLayer Recurrent Neural Network Output Layer. Handles calculation of gradients etc for various objective functions. Functionally the same as OutputLayer, but handles output and label reshaping automatically. Input and output activations are same as other RNN layers: 3 dimensions with shape [miniBatchSize,nIn,timeSeriesLength] and [miniBatchSize,nOut,timeSeriesLength] respectively.

Uses of BaseOutputLayer in org.deeplearning4j.nn.layers.training

Subclasses of BaseOutputLayer in org.deeplearning4j.nn.layers.training

Modifier and Type	Class and Description
class	CenterLossOutputLayer Center loss is similar to triplet loss except that it enforces intraclass consistency and doesn't require feed forward of multiple examples.